Manufacturers process and test semiconductor or integrated circuit (“IC”) devices using various types of automated machinery. Before IC devices are shipped to wholesalers or consumers, they must be tested for performance and inspected for physical defects. One physical defect that is important to identify is the presence of bent pins on IC devices having a pin grid array (“PGA”).
Generally, mechanical systems or basic camera systems are employed to identify bent pins. However, current mechanical and camera systems are limited in their ability to detect bent pins accurately. Conventional mechanical systems lack the ability to provide information beyond simply identifying bent pins. In addition, basic vision systems that use cameras to detect bent pins are limited in their effectiveness because generally, the contrast between a tip of a pin and the pin base is poor. The poor contrast between a tip of a pin and the pin base also prevents basic vision systems from accurately detecting bent pins on a pin grid array.
Other conventional systems have operational drawbacks as well. For example, one conventional camera system uses a generic lighting system in conjunction with blob analysis. In a binary image, a blob is an area of pixels with the same logical state. Blob analysis is used to detect and make measurements of blobs in an image. However, the lighting used in blob analysis systems is not uniform, which results in less than reliable detection results. Yet another known inspection system implements 3D detection on a PGA. However, due to the complexity needed to obtain a three-dimensional image, this method is unnecessarily expensive and therefore an undesirable option.
Therefore, it would be desirable to provide an inexpensive system that is capable of accurately detecting bent pins on a PGA and providing detailed information about individual pins in a PGA.